risk and return analysis of listed financial companies in

Open Science Journal – March 2020 1

RESEARCH ARTICLE

Risk and Return Analysis of Listed Financial

Companies in Ghana (A Study of Cal Bank,

Ecobank GH Ltd, Ghana Commercial Bank

(GCB) and Standard Chartered Bank

(SCB))

Gideon Kweku Appiah1*, Lin Lan Xiao1

1Central Michigan University, United States of America

*Corresponding author: Gideon Kweku Appiah: [email protected]

Abstract:

Citation: Appiah G.K., Xiao L.L. (2020) Risk and Return Analysis of Listed Financial Companies in Ghana( A Study of Cal Bank, Ecobank GH Ltd, Ghana Commercial Bank ( GCB) and Standard Chartered Bank (SCB)). Open Science Journal 5(1) Received: 22nd July 2019 Accepted: 27th January 2020 Published: 2nd March 2020 Copyright: © 2020 This is an open access article under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: The author(s) received no specific funding for this work Competing Interests: The author have declared that no competing interests exists.

Globally, Investors as well as businessmen and women are very

optimistic about the future and therefore defer current use of

resources for use at a later period with a higher expected rate of

return. This is not so different in the case of Ghana. The main

objective of the study is to analyse the risk and return of listed

financial companies in Ghana. A sample of four financial

companies listed on the Ghana Stock Exchange (Cal Bank

Limited, Ecobank Ghana Limited, GCB Bank Limited and

Standard Chartered Bank Ghana Limited) were selected and

financial ratio (return on equity, return on asset, current ratio,

quick ratio and financial leverage) computed using excel and

analyzed using STATA. The study fitted a Pooled Ordinary

Least Square (OLS) and Least Square Dummy Variable (LSDV)

regression model with fixed effect model since fixed effect was

tested to be statistically significant in the model. Empirical

analysis of the data revealed that Banks with high risk levels

proved to have a higher profitability as compared to the other

banks under study. Standard Chartered Bank Ghana Limited

and Ecobank Ghana Limited showed the highest levels of

profitability, with Standard Chartered Bank Ghana Limited

topping the charts in most years. However, on average, Cal

Bank Ghana recorded the lowest rates of profitability.

Also, a positive relationship existed between profitability (return

on equity) and current ratio and financial leverage whilst an

inverse relationship between return on equity and quick ratio.

Overall model for both the Pooled OLS and the LSDV regression

model tested to be statistically significant and a greater

percentage (99.99%) of the total variability in return on equity

was explained by the independent variables (return on asset,

current ratio, quick ratio and financial leverage).

Open Science Journal Research Article


Keywords: Risk, Return, Pooled OLS regression model, LSDV regression

model.

Introduction

Background of the study

There is no single definition of risk. Economists, behavioral scientist, risk

theorists, actuaries and financial analyst have their own concept of risk. Based on

this, George E. Rejda, (2014) defined risk as the uncertainty concerning the

occurrence of loss. Individuals and corporate bodies make investment decisions

which have a significant influence on the productivity of a firm. These decisions

however must be made for a business to be run and may hold a positive outcome

or an undesired one. A return (financial return), in its simplest terms, is the

money made or lost on an investment (AG1, 2015). A return can be expressed

nominally as the change in the value of an investment over time and it is also

expressed as a percentage derived from the ratio of profit to investment. Globally,

Banks play an important role in supporting economic growth and development.

This has in effect proved to be more volatile than the pure diversified equity

funds which make some of them a high risk proposition (Naveen, 2016).

Ghana in recent times (2010-2019) is facing diverse challenges in the banking

industry. Bank of Ghana (BOG), the Central Bank in Ghana on the urge of

putting measures in place to prevent bank runs in the mid 2017 led to the revoke

of the license of several banks, two of which were classified as Ghanaian owned

banks, UT Bank and Capital Bank. According to the AGI report, BOG classified

these two banks as “heavily deficient in capital and liquidity” which has caused

loss of confidence in most banks in Ghana as it is riskier to invest in those banks.

There has been different reform proposals in the banking sector globally to

enhance growth in the sector one of which is the Bank of International

Settlements (1999) which have been made with the objective of improving bank

regulation, and several others after the global financial crisis of 2007–2009

(Accenture, 2000).

Between 2018 and 2019, seven more banks in Ghana lost their license for

other regulatory breaches which was associated with mismanagement and

unavailability of their Stated Capital when BOG increased minimum reserved

requirement to GHS400,000,000. These banks losing their license is an indicator

of high risk. (Boahene et al., 2012) seeking evidence of the relationship between

credit risk and profitability of some selected banks in Ghana revealed a positive

and significant one.

Modern Portfolio Theory (MPT) and Capital Asset Pricing Model (CAPM)

are some of the financial theories which support the opinion that risk and return

play an important role in arriving at good investment making decisions.

regression model tested to be statistically significant and a

greater percentage (99.99%) of the total variability in return on

equity was explained by the independent variables (return on

asset, current ratio, quick ratio and financial leverage).



The MPT attempts to amplify the expected return of a portfolio for a given

amount of portfolio risk by purposefully choosing specific proportions of various

assets. MPT takes the assumption that investors are generally risk averse,

meaning that given two different portfolios giving the same expected return,

investors will prefer the one which has a lower risk (Markowitz, 1952).

According to the Global risk management banking report 2017, Investors are

skeptical when entering an investment that have liquidity issues. There is an

urgent need for financial institutions and risk regulators to exercise due diligence

when handing liquidity issues. The collapse of these banks in Ghana brought

about controversies with different schools of thought. Some believing that it’s a

step in the right direction by the Central Bank to ensure economic stability,

others see the initiative to be of political conundrum. According to Nana Addo

Dankwa Akuffo-Addo, the President of the Republic of Ghana, the ongoing

exercise by the Bank of Ghana was not as a result of his government collapsing

certain banks in the country but instead, geared towards cleansing the sector to

pave way for indigenous banks to compete with foreign banks.

In mid-2018, when the financial sector in Ghana was recovering from its

crises, Credmap technology, a civic movement in Ghana dedicated to the use and

promotion of various technologies to encourage truth and integrity in public life

issued a public statement on a survey conducted on ranking of Commercial Banks

in Ghana using the Ghana Banking Credibility Index. Standard Chartered Bank

emerged as the most credible bank.

Problem Statement

Investors defer current use of resources for use at a later period in the future,

with higher expected rates of return (Kalyan & Subramanyam, 2018). The

problem however is, which company they should invest in to obtain maximum

returns without using too much capital and losing out on investments.

Theoretically whilst financial leverage and other risk factors are used to generate

revenue and increase profit margins, larger indebt of these indicators can cause

disinvestment and inhibit profitability. MPT takes the assumption that investors

are generally risk averse, meaning that given two different portfolios giving the

same expected return, investors will prefer the one which has a lower risk

(Markowitz, 1952).

Research on Risk and return analysis of listed financial companies in the

developed countries has been undertaken which has in effect educated citizen on

the financial institutions they should invest in. Even in that case, not much has

been done pertaining to risk indicators such as Quick ratio and financial leverage.

Also, not much of such works have been done in Africa and Ghana to be precise.

This has rendered some inadequacies in the financial sector due to the lack of

knowledge about risk and return on behalf of the citizenry.

In Ghana, there are quite several avenues for investments. The measurement

of financial institutions’ efficiency is crucial because it helps investors and the

citizenry to know the performance (Ross, Westerfield, & Jordan, 2003). A lot of

investors pay much attention to their returns without giving relevance to risk

(Ketchen et al., 2018). With every level of returns, there is a given level of risk

associated with it. Therefore, to select a company to invest in, it is important to

find out how the company is faring as compared to other companies by taking

both risk and return into consideration. This study is therefore aimed at assessing



the financial risk and return of financial institutions listed on the Ghana Stock

Exchange using financial ratios (liquidity and profitability ratios).

Objectives of the study

The general objective of the study is to assess the financial risk and return of

listed financial companies in Ghana

Specifically;

• To study the trend of financial risk and return indicators of the listed

companies understudy.

• To formulate a model that can predict the financial return of the listed

companies understudy.

• To test if the level of financial risk has a significant influence on the

returns of the company.

Significance of the study

• The study of risk and return would help investors to know the best

performing financial institution on the Ghana Stock Exchange

• It will add up to existing literature on risk and return analysis of listed

companies in Ghana and Sub-Saharan Africa at large.

• It would help individual business men and women as well as co-operate

bodies to make informed decisions on which company to invest.

• It would help the banking institutions restructure and make policies that

will help reduce risk and increase returns.

Literature review

Theoretical and empirical review

Literature review on performance evaluation of financial institution is

enormous. Various studies have been carried out in developed and developing

countries. There are studies on the Ghana Stock Exchange (GSE) to evaluate the

performance of financial institutions over time due to its significant contribution

to academia and industry.

The economics of banking literature acknowledges various determinants of

bank profitability. The profitability of a bank is most crucial to its growth and

development. Some of these determinants include the size of the bank; the extent

to which the bank is diversified; the attitude of the bank’s owners and managers

towards risk; the bank’s own characteristics; and the level of external competition

the bank encounters. These, in one way or the other, affect the financial position

of the institution (JOHN GODDARD, 2004).

(Jensen Michael C., Blank & Sholes, 1972) took efforts to investigate the stock

market as an efficient and the purpose for which they took all scripts of New

York Stock Exchange and divided into ten portfolios with the span of 35 years.

The study found that higher risk portfolios fetched higher return and further they

found that the stocks those of belonging to the category of lower risk were



undervalued whereas the stocks those of belonging to the category of higher risk

were overvalued.

(Strahan, 1997) investigated the role of diversification in US banking and

found that large banks had lower capital reserves and were more active than their

specialized counterparts in high-risk lines of business such as derivatives.

According to Basel committee on Bank supervision (2008), the basic role of banks

during maturity transformation of short-term deposits into long-term loans makes

them essentially vulnerable to liquidity risk of the bank as an institution and the

market as a whole (systemic).

(Singh, 1986) disclosed the basic rules for selecting the company to invest in.

She opined that understanding and measuring return and risk is fundamental to

the investment process. According to her most investors are 'risk averse'. To have

a higher return, the investor must face greater risk.

(Jones, 1996) reviewed how to estimate security return and risk. To estimate

returns, the investors must estimate cash flows the securities are likely to provide.

Also, investors must be able to quantify and measure risk using variance or

standard deviation. Variance or standard deviation is the accepted measure of

variability for both realized returns and expected returns. He suggested that the

investors should use it as the situation dictates. He revealed that over the past 12

years, returns in stocks, bonds, etc. have been normal. Blue-chip stocks have

returned an average of more than 16% per year. He warned that the investors

who believe that these rates will continue in the future also will be in trouble.

This existence of influential observation is a positive outcome since it provides

evidence for a link between economic activity and cross‐sectional variation in

average returns. According to (Shoaib Khan, 2012) “non‐normality can occur

when the sample contains outlier observations that are extreme by virtue of their

absolute size”. Also, outliers can crop up due to errors in the data or extreme

observation. (Shoaib Khan, 2012), given the observed October 1987 return as an

example. It is not always easy to identify outliers; however, plotting the data will

make them more obvious. Outliers can be treated by OLS estimation or contained

within the OLS estimation. The outlier can be excluded from the sample and a

dummy variable included to reflect the consequence of the outlier.

Methodology

Data source and description of the data

A secondary data for this study is obtained from the Ghana Stock exchange

website over the years from 2007 to 2016. This data is the financial statement of

all companies listed on the stock market. Investment indicators such as Returns

on Assets (ROA), Returns on Equity (ROE), Current Ratio (CR) and Quick

Ratio (QR) is obtained calculated from the data and used for analysis. Returns

on Equity (ROE) measures profitability of a firm whilst risk determinants are the

other variables under study.



Description of variables

A brief description of the variables is presented in the sub-sections below:

Returns on Equity (ROE): This is the amount of net income returned as a

percentage of shareholders’ equity. Return on equity measures a corporation's

profitability by revealing how much profit a company generates with the money

shareholders have invested. (Investopedia)

Returns on Assets (ROA): This is an indicator of how profitable a company is

relative to its total assets. ROA gives an idea as to how efficient management is

at using its assets to generate earnings. Calculated by dividing a company's

annual earnings by its total assets. (Investopedia)

Current Ratio (CR): This compares current assets with obligations which will

be due in the same period (i.e. total current liabilities) and it indicates whether

there are enough short-term assets to meet the short-term liabilities.

Quick Ratio (QR): This shows that, provided creditors and debtors are paid

at approximately the same time, a view might be made as to whether the

business has enough liquid resources to meet its current liabilities.

Financial Leverage (FL): This is a measure of how much assets a company

holds, relative to its equity. It measures the amount of equity used by financial

institutions to meet debt obligations as they fall due.

Statistical tools to be used

Panel Data Modelling

Panel data, also known as longitudinal data or cross-sectional time series data,

is data derived from a number of observations over time on a number of cross-

sectional units such as individuals, households, firms, cities, states or countries. In

this study, panel data are analyzed. Specifically, economic and investment

indicators such as Returns on Assets (ROA), Returns on Equity (ROE), Current

Ratio (CR), Quick ratio (QR) and Financial Leverage (FL) for four commercial

banks in Ghana over the years from 2007 to 2016 are investigated. Therefore it is

a time series panel with sample size 40.

The study begins by fitting a Pooled Ordinary Least Square (OLS) regression

model. Then the Least Square Dummy Variable (LSDV) regression model is

employed. It is worth mentioning that we have long panel, i.e. T>n, to take into

account possible non-stationary in our data we use natural log of each variable

instead of level data in our regression model.

Pooled Ordinary Least Square (OLS)

The Pooled Ordinary Least Square (Pooled OLS) is applied as the benchmark.

Assuming individual effect (time specific effect) does not exist, the Pooled OLS is

able to produce efficient and consistent estimates.

The Pooled OLS model is as following:

(1)

Where



= constant

= random error component.

= the regressors in the model

the coefficients of the regressors in the model.

Least Square Dummy Variable Regression model

The Least Square Dummy Variable (LSDV) regression model, an OLS with a

set of dummies, is a fixed effect model used in panel data analysis which allows

individual differences in intercepts (heterogeneity). In this study we introduce

three dummy variables to represent the individuality of the commercial banks.

The LSDV model is as following:

(2)

where

constant

a set of dummy variables with

= random error component.

= the individual regressors in the model

The coefficient of the dummy variables in the model

The coefficient of the regressors in the model.

Specifically, is the intercept representing the expected profitability rate

given that there are no regressors and no dummies in the model.

are the slopes of , and , respectively which

measure the expected changes in profitability for per percentage change in the

changes in corresponding independent variable given that all other regressors and

dummies are constant in the model. may take positive or negative

values. A negative value of shows that profitability rate would

decrease by if their corresponding individual regressor increases

by one percentage unit. On the other hand, a positive value of

shows that profitability rate would increase by units if their

corresponding individual regressor increases by one percent.

It is worth mentioning that are three dummy variables

created which represent CAL Bank Ghana Ltd (CAL), Ecobank Ghana Ltd

(EBG), Ghana Commercial Bank (GCB) and Standard Chartered Bank (SCB)

respectively. On the other hand, are parameters (mean profitability) of

the group dummy variables. for instance is the real impact of profitability

rate that CAL Bank has on the group constant (Profitability rate). This value is

added to the group coefficient to have a new constant for a defined regression

model for CAL Bank. This applies to other banks where , represent CAL Bank Ghana Ltd (CAL), Ecobank Ghana Ltd (EBG), Ghana

Commercial Bank (GCB) and Standard Chartered Bank (SCB) respectively in

this study.



Analysis

Preliminary Analysis

Table 1 reports descriptive statistics of the variables in this study.

Table 1: Descriptive Statistics of the variables

Variables

understudy

Mean Standard

deviation

Skewness Kurtosis Minimum Maximum

Ret. on Equity .2917894 .1159091 -0.39966 2.447223 .0143267 .4917748

Return on Asset .0390008 .0167536 -0.20142 2.342357 .003039 .0696098

Current Ratio 1.046622 .1219913 -1.35721 4.20164 .6666762 1.182895

Quick Ratio .2737285 .1591932 -0.09141 2.830976 -.0800785 .5872572

Fin. Leverage 6.810343 1.752554 1.147168 4.793988 4.455894 12.80369

Financial statements were obtained from the Ghana Stock Exchange for the

companies under study. Financial risk and return indicators such as Return on

Equity, Return on Asset, Current Ratio, Quick Ratio and Financial Leverage

Ratio was computed for each company over the years under consideration.

Further analysis of the study revealed, the minimum and maximum return on

equity recorded over the years under consideration was 0.143267 and 0.491778

respectively with an average return on equity and standard deviation recorded

over the years considered was 0.2917894 and 0.1159091 respectively. The negative

value of skewness suggests that the sample is negatively skewed; as the value of

kurtosis is smaller than 3, it indicates that the sample has lighter tails than a

normal distribution.

The minimum and maximum Return on Assets recorded over the years

considered was 0.003039 and 0.0696098 respectively, with an average and

standard deviation of 0.03008 and 0.0167536, respectively. Similarly as return on

equity, the sample for return on assets is also negatively skewed with a lighter

tails.

On the other hand, the minimum and maximum recorded on Current Ratio

was 0.666762 and 1.182895 respectively. Whereas the average and standard

deviation 1.046622 and 0.1219913 respectively. Obviously, the sample for current

ratio is heavily negatively skewed with much heavier tails comparing to a normal

distribution.

The minimum and maximum Quick Ratio recorded over the years considered

was -0.0800785 and 0.5872572 respectively, with an average and standard

deviation 0.2737285 and 0.1591932 respectively. The sample for this variable is

also negatively skewed with a lighter tails.

The Financial Leverage Ratio over the years considered recorded a respective

minimum and maximum of 4.455894 and 12.80369, with an average of 6.810343

and a standard deviation of 1.752554. Unlike other variable in this study, the

Financial Leverage Ratio is significantly positively skewed with a much heavier

tails comparing with a normal distribution.



Graphical Representation of Profitability (Return on Equity)

Time series plots for all the variables in this study are reported in Figures 4.1-

4.5. By observing the pattern of these graphs, we aim to study the trend of

financial risk and return indicator of the listed companies understudy (objective 1

in our study).

Figure 4.1: Time series plot of Return on Equity of the bank from the year

2007 to 2016

Figure 4.1 shows a time series plot representing the profitability (Return on

Equity) over the ten-year period of the four companies under study, Cal Bank

Limited, Ecobank Ghana Limited, GCB Bank Limited and Standard Chartered

Bank Ghana Limited. Standard Chartered Bank Ghana Limited had recorded a

relatively higher return on equity over the years from 2007 to 2014. However,

they had a heavy decline in the year 2015. GCB Bank Limited on the other hand

has a relatively lower return on equity over the years from 2007 to 2011. During

2011 to 2013, GCB Bank Ltd had a massive increase in their return on equity,

but had a decline in subsequent years. CAL Bank has been experiencing a

fluctuation in their return on equity. They recorded an increase in return on

equity between the years from 2011 to 2014. However, over the years under

consideration, CAL Bank recoded the lowest return on equity amongst the four

companies and this occurred in the year 2016. In the year 2008, Ecobank Ghana

Ltd recorded the highest return on equity amongst the four companies, then after

a short time period decline, it experienced an upward trend till 2014, following by

a slightly decline during 2015-2016 time period. Ecobank Ghana Ltd’s return on

equity has been higher than that of CAL bank over the whole sample period.



Figure 4.2: Time series plot of Return on Asset of the bank from the year 2007

to 2016

Figure 4.2 displays return on assets of the four companies. Similarly as return

on equity, CAL Bank recorded the lowest return on asset in the year 2016 over

the ten-year period. GCB Bank, on the other hand, despite their lower values in

the early years had a massive increase in return on asset during 2011- 2013.

Overall all four companies experienced a downward trend during 2013-2016 time

period except that Standard Chartered Bank Ghana Limited had a significant

increase in return on assets during 2015-2016.

Figure 4.3: Time series plot of Current Ratio of the bank from the year 2007

to 2016

Current ratio time series plots for the four companies are reported in Figure

4.3. Current ratio has been close amongst CAL Bank Ghana Ltd, Ecobank

Ghana Ltd and GCB Bank. CAL Bank however experienced a significant decline

during 2015-2016 time period whereas the other two companies were relatively



stable during the whole sample period. On the other hand, over the ten-year

period Standard Chartered Bank recorded the lowest current ratio comparatively.

Figure 4.4: Time series plot of Quick Ratio of the bank from the year 2007 to

2016

Figure 4.4 represents Quick Ratio time series plots for the four companies.

CAL Bank over the sample period recorded the highest Quick ratio compared to

the other companies with Standard Chartered Bank recording relatively lower

values. There was a massive turn in the year 2016 as CAL Bank recorded the

lowest Quick ratio while it recorded the highest amongst all the other banks in

the year 2015. On the other hand, SCB declined significantly during 2014-2016

time period. Both EGH and GCB exhibit relatively smooth pattern during the

whole sample period.



Figure 4.5: Time series plot of Financial leverage of the bank from the year

2007 to 2016

In terms of financial leverage reported in Figure 4.5, Ecobank Ghana Ltd

recorded the highest amongst the other banks at the beginning of the sample

period but had a decline from 2008 to 2009; it then started to increase from 2009

and continued to lie above the other banks. GCB Bank Ltd had a massive

increase in financial leverage in the year 2011 after a persistent increase in the

earlier years but experienced a decline in the years after 2011. The values of

financial leverage for this company continued to be the lowest among four

companies from 2014.

Overall we observe CAL Bank suffered significant decline during 2016 time

period for most variables, the decrease in the performance of CAL Bank in 2016

is attributed to the instability in the banking industry associated with Bank runs

as customers reduce their investment with the company. According to the AGI

2017 report, these affected their stocks which in the long run affected their return

on assets, return on equity and other financial indicators.

The Pooled Ordinary Least Square (OLS) regression model.

Table 2 reports the Pooled OLS regression result, which is used as a

benchmark model to predict the financial return of the listed companies

understudy (objective 2 in this study). Column 2 represents the coefficients;

whereas columns 3 and 4 display t statistics testing the significance of each

individual independent variable, and the associated p-value, respectively.

Specifically, if all the risk factors are zero, the estimated profitability will be

0.3739463%. There exists positive relationships between profitability and return

on asset, Current Ratio and financial leverage ratio, but an inverse relationship

exists between profitability and the quick ratio. Specifically, the profitability

would increase by 0.9981604% when return on asset increases by one percent; one

percentage increase in Current Ratio will lead to 0.0224569% increase in

profitability; and the profitability would increase by 0.872142% for every one



percentage increase in Financial Leverage; on the other hand, one percentage

increase in Quick Ratio will lead to 0.0030508% decease in profitability.

One-sample t-test is applied to test the significance of individual financial risk

variable in the Pooled OLS regression (objective 3 in this study).The t-statistics

are relatively high with the associated p-value smaller than 10 percent level of

significance for most independent variables except for the Quick Ratio, suggesting

that Return on Asset, Current Ratio and Financial Leverage significantly affect

the profitability whereas Quick Ratio does not play a significant role in

explaining the profitability.

Table 2: The Pooled Ordinary Least Square (OLS) regression model.

Variables Coefficient t-statistic P > | t |

Return on Asset 0.9981604

(0.0015385)

648.79 0.000*

Current Ratio 0.0224569

(0.0119319)

1.88 0.069**

Quick Ratio -0.0030508

(0.0019236)

-1.59 0.123

Financial Leverage 0.872142

(0.0034644)

251.74 0.000*

Constant 0.3739463

(0.0068525)

54.57 0.000*

*Significant p – value = 0.0000 𝐑𝟐 = 0.9999 𝐀𝐝𝐣 𝐑𝟐 = 0.9999

The Least Square Dummy Variable (LSDV) regression model.

Table 3 presents the LSDV regression result, which takes into account fixed-

effect among companies in predicting the financial return of the listed companies

understudy (objective 2). Column 2 represents the coefficients; whereas columns 3

and 4 display t statistics testing the significance of each individual independent

variable, and the associated p-value, respectively. It is worth mentioning that

CAL Bank Limited was omitted from the study with the LSDV regression models

due to collinearity.

Applying the LSDV when all the risk factors as well as the dummies are zero,

the estimated profitability will be 0.3651051%, similar to the Pooled OLS result.

There exists positive relationships between profitability and return on asset,

Current Ratio and financial leverage ratio, but an inverse relationship exists

between profitability and the quick ratio. Hence the signs of coefficients for these

risk factors are consistent to those applying the Pooled OLS procedure.

Specifically, the profitability would increase by 0.9985742% when return on

asset increases by one percent; one percentage increase in Current Ratio will lead

to 0.0469455% increase in profitability; and the profitability would increase by

0.8764547% for every one percentage increase in Financial Leverage; on the other

hand, one percentage increase in Quick Ratio will result in 0.0030103% decease in

profitability.



Similarly as the Pooled OLS, one-sample t test is applied to test the

significance of individual financial risk variable in the LSDV regression (objective

3 in this study). The t-statistics are relatively high with the associated p-value

smaller than five percent level of significance for most independent variables

except for the Quick Ratio, suggesting that Return on Asset, Current Ratio and

Financial Leverage significantly affect the profitability whereas Quick Ratio does

not play a significant role in explaining the profitability.

Regarding the heterogeneity among the companies, we find Ecobank Ghana

Limited has a baseline intercept of profitability of -0.002731% which lowers the

constant of the LSDV regression model. This is however statistically insignificant

at even 10% level as the P-value equaling to 0.215, indicating the heterogeneity

for EcoBank Ghana Limited is insignificant. The GCB Bank has a baseline

intercept of 0.0007942% which further increased the constant of the LSDV

regression model, but it was not statistically insignificant at 10% alpha level

given the P-value 0.715. On the other hand, the Standard Chartered Bank Ghana

Limited has a baseline intercept of 0.0052034% which was above the constant of

the model. This is again not statistically significant at 10% alpha level since P-

value is 0.150. Overall we conclude that the heterogeneity does not significantly

exist among the companies in this study, and the Pooled OLS and LSDV produce

similar regression results.

Table 3: The Least Square Dummy Variable (LSDV) regression model.

Variables Coefficient t-statistic P > | t |

1.CAL Bank Ghana

Ltd (Dummy)

0 (omitted) 0 0

2. Ecobank Ghana Ltd.

(Dummy)

-0.002731

(0.0021554)

-1.27 0.215

3. Ghana Commercial

Bank. (Dummy)

0.0007942 (0.002151) 0.37 0.715

4. Standard Chartered

Bank. (Dummy)

0.0052034

(0.0035227)

1.48 0.150

Return on Asset

0.9985742

(0.0015939)

626.50 0.000*

Current Ratio

0.0469455

(0.0173905)

2.70 0.011*



Quick Ratio

-0.0030103

(0.002199)

-1.37 0.181

Financial Leverage

0.8764547

(0.0037307)

234.93 0.000*

Constant 0.3651051

(0.0081218)

44.95 0.000*

*Significant p – value = 0.0000 𝐑𝟐 = 0.9999 𝐀𝐝𝐣 𝐑𝟐 = 0.9999

Comparative statics between the pooled OLS and the Least Square Dummy Variable (LSDV) regression model.

Comparative statics between the pooled OLS and the Least Square Dummy

Variable (LSDV) regression model.

Variables Pooled OLS LSDV Regression Model

Number of observations 37 37

F( n, N) 99999.00 71913.16

Prob > F 0.0000 0.0000

R-squared 0.9999 0.9999

Adj R-squared 0.9999 0.9999

Root MSE 0.00405 0.00382

Both Pooled Ordinary Least Square Regression Model (OLS) and the Least

Square Dummy Variable Regression Model (LSDV) tested to be statistically

significant since the Pooled OLS revealed an F-statistic of 99999.00 with a P-

value of 0.0000<0.050 and the LSDV Regression Model revealed an F-statistic of

71913.16 with a P-value of 0.0000<0.050.

They are both statistically significant at 1%, 5% and 10% level of significance.

Also, in both models 99.99% of the total variability in profitability was

explained by the independent variables (return on assets, current ratio, quick

ratio and financial leverage).



Conclusion and Recommendation Conclusion

The study looked at the analysis of risk and return of listed financial

companies, namely Cal Bank Limited, Ecobank Ghana Limited, GCB Bank

Limited and Standard Chartered Bank Ghana Limited. Financial ratios (liquidity

and profitability ratios) were obtained from annual financial statements over a

ten-year period (2007 to 2016). GCB Bank Limited recorded the highest

profitability rate over the ten-year period in 2013, but on average, Standard

Chartered Bank Ghana Limited recorded the highest rates of profitability. The

lowest profitability rate was recorded by Cal Bank Limited in the year 2016.

The Pooled Ordinary Least Square and the Least Square Dummy Variable

Regression model were used in assessing the financial risk and return of the listed

companies, and the variables of the models proved to be statistically significant.

Risk had a significant influence on the returns of the companies.

Recommendation

• Investors have independent risk levels. In order to gain high returns on

investments, investors should not only have to look at the profitability of

the company but take a close look at the risk of the company.

• Investors are advised to invest based on how risk averse they are or how

much risk they are willing to take in. Investors who have a high risk

appetite may invest in banks that have a high risk with equally high

returns such as Standard Chartered Bank Ghana Limited.

• Stock prices over the years should be taken into consideration in the

analysis of risk and return analysis, since the price of a stock also affects

how much an investor is willing to make.

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